An Overview of Smart City Planning—The Future Technology

Abstract

The fast development of metropolitan communities around the globe has created new issues for individuals’ everyday life, such as contamination, community safety, and traffic congestion. Smart communities have indeed been established using emerging innovations to handle this massive development. The concept of “smart cities” arose as a result of recent technology breakthroughs, with the goal of increasing city economy and quality of life. As it turns out, new ideas and concepts have not kept up with the rate of technology advancements and their applications in modern life. In the current environment, machine learning (ML) and deep learning (DL) technologies have aided the growth of models in various elements of urban and smart city development plans, forecasting, and risk assessment. Deep learning (DL), a new area of artificial intelligence (AI) and machine learning (ML) has recently demonstrated the potential for increasing the efficiency and performance of IoT big data analytics. In this overview, we provide a review of the literature regarding the use of AI and ML to develop smart cities. The purpose of this chapter is to provide an overview and discussion of cybersecurity, smart buildings, and important research on security in those technologies. The current study emphasizes on the critical parts of a city of the future, such as smart grid, building automation, smart environment, smart administration, and smart market, in order to achieve this goal. Smart mobility and smart health are two examples of smart technologies. An overview of deep learning method and cybersecurity initiatives is covered, as well as innovation correlations in smart urban. © 2023 Elsevier Inc. All rights reserved.